Volume 23, Issue 8 (August 2023)                   Modares Mechanical Engineering 2023, 23(8): 475-483 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Tahmasbi V, Aeinehbandy S, Baghi M H, Sousanabadi Farahani A. Sensitivity analysis modeling and optimization of cutting Forces and stool wear in milling of aluminum matrix composite. Modares Mechanical Engineering 2023; 23 (8) :475-483
URL: http://mme.modares.ac.ir/article-15-67470-en.html
1- Arak University of Technology , tahmasbi@arakut.ac.ir
2- Arak University Of Technology
3- Arak University
Abstract:   (1914 Views)
Advances in many engineering fields depend on materials with appropriate properties. The use of metal-matrix composites is rapidly growing as a suitable alternative to conventional materials due to their strength-to-weight ratio, resistance to wear and creep, etc. Machining of metal-based composites is a difficult task due to the presence of very abrasive reinforcing particles in its based metal. Therefore, it is necessary to investigate the factors affecting these materials. In this research, a methodical study has been conducted to investigate the effect of the parameters of spindle  speed, feed rate, depth of cut and the percentage of reinforcing particles on the behavior of cutting force and tool wear using experimental design methods, modeling and statistical sensitivity analysis methods. . Detailed analysis of behaviors has been done by providing statistical regression equations and optimization by Deringer's method and E-Fast-Sensitivity Analysis. According to the obtained results, the cutting depth had the greatest effect on the machining force. Also, cutting speed with 77%, advance rate with 9% percent and cutting depth and weight percent of reinforcing particles with 7% percent are other parameters affecting tool wear in the milling process of this composite.
Full-Text [PDF 969 kb]   (602 Downloads)    
Article Type: Original Research | Subject: Machining
Received: 2023/02/12 | Accepted: 2023/06/20 | Published: 2023/08/1

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.